Passion at the heart of musicians’ well-being
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article proposes that passion for music is an essential element in explaining the well-being of musicians. Based on the PERMA model of well-being and on research on passion for music, this article posits that being passionate about music, and more specifically holding a harmonious type of passion (HP), reduces music-related anxiety and enhances musicians’ life satisfaction, sense of psychological growth and mastery. Furthermore, it is expected that holding an obsessive passion (OP) toward music might thwart musicians’ well-being through increased musical anxiety. These hypotheses were tested with 225 trainee and expert classical musicians. In order to provide a valid measure of passion for music, the Passion Scale for Music (PSM) was first validated. Structural Equation Modelling (SEM) results provided support for the hypothesis that musicians who are passionate about music, and even more those who are HP, experience increased well-being, while OP does not contribute to musicians’ well-being. The relationships between passion and well-being in musicians were moderate to strong, confirming that the types of passion musicians hold is a central element in explaining their well-being. The article concludes that being passionate about music acts as a “sparkle” that brightens musicians’ lives with regards to their global well-being experience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.033 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it